Search

Upcoming submillimeter wave satellite missions require an improved understanding of sea ice emissivity to separate atmospheric and surface microwave signals under dry polar conditions. This work investigates hectometer-scale observations of airborne sea ice emissivity between 89 and 340 GHz , combined with high-resolution visual imagery from two Arctic airborne field campaigns that took place in summer 2017 and spring 2019 northwest of Svalbard, Norway. Using k -means clustering, we identify four distinct sea ice emissivity spectra that occur predominantly across multiyear ice, first-year ice, young ice, and nilas. Nilas features the highest emissivity, and multiyear ice features the lowest emissivity among the clusters. Each cluster exhibits similar nadir emissivity distributions from 183 to 340 GHz. To relate hectometer-scale airborne measurements to kilometer-scale satellite footprints, we quantify the reduction in the variability of airborne emissivity as footprint size increases. At 340 GHz , the emissivity interquartile range decreases by almost half when moving from the hectometer scale to a footprint of 16 km , typical of satellite instruments. Furthermore, we collocate the airborne observations with polar-orbiting satellite observations. After resampling, the absolute relative bias between airborne and satellite emissivities at similar channels lies below 3 %. Additionally, spectral variations in emissivity at nadir on the satellite scale are low, with slightly decreasing emissivity from 183 to 243 GHz , which occurs for all hectometer-scale clusters except those predominantly composed of multiyear ice. Our results will enable the development of microwave retrievals and assimilation over sea ice in current and future satellite missions, such as the Ice Cloud Imager (ICI) and EUMETSAT Polar System – Sterna (EPS–Sterna). [ABSTRACT FROM AUTHOR]

Global warming is amplified in the Arctic. However, numerical models struggle to represent key processes that determine Arctic weather and climate. To collect data that help to constrain the models, the HALO–(AC) 3 aircraft campaign was conducted over the Norwegian and Greenland seas, the Fram Strait, and the central Arctic Ocean in March and April 2022. The campaign focused on one specific challenge posed by the models, namely the reasonable representation of transformations of air masses during their meridional transport into and out of the Arctic via northward moist- and warm-air intrusions (WAIs) and southward marine cold-air outbreaks (CAOs). Observations were made over areas of open ocean, the marginal sea ice zone, and the central Arctic sea ice. Two low-flying and one long-range, high-altitude research aircraft were flown in colocated formation whenever possible. To follow the air mass transformations, a quasi-Lagrangian flight strategy using trajectory calculations was realized, enabling us to sample the same moving-air parcels twice along their trajectories. Seven distinct WAI and 12 CAO cases were probed. From the quasi-Lagrangian measurements, we have quantified the diabatic heating/cooling and moistening/drying of the transported air masses. During CAOs, maximum values of 3 K h -1 warming and 0.3 g kg -1 h -1 moistening were obtained below 1 km altitude. From the observations of WAIs, diabatic cooling rates of up to 0.4 K h -1 and a moisture loss of up to 0.1 g kg -1 h -1 from the ground to about 5.5 km altitude were derived. Furthermore, the development of cloud macrophysical (cloud-top height and horizontal cloud cover) and microphysical (liquid water path, precipitation, and ice index) properties along the southward pathways of the air masses were documented during CAOs, and the moisture budget during a specific WAI event was estimated. In addition, we discuss the statistical frequency of occurrence of the different thermodynamic phases of Arctic low-level clouds, the interaction of Arctic cirrus clouds with sea ice and water vapor, and the characteristics of microphysical and chemical properties of Arctic aerosol particles. Finally, we provide a proof of concept to measure mesoscale divergence and subsidence in the Arctic using data from dropsondes released during the flights. [ABSTRACT FROM AUTHOR]

The HALO–(AC)3 aircraft campaign was carried out in March and April 2022 over the Norwegian and Greenland Seas, the Fram Strait, and the central Arctic Ocean. Three research aircraft, the High Altitude and Long Range Research Aircraft (HALO), Polar 5, and Polar 6, performed 54 partly coordinated research flights on 23 flight days over areas of open ocean, the marginal sea ice zone (MIZ), and the central Arctic sea ice. The general objective of the research flights was to quantify the evolution of air mass properties during moist and warm air intrusions (WAIs) and cold air outbreaks (CAOs). To gain a comprehensive data set, the three aircraft followed different strategies. HALO was equipped with active and passive remote sensing instruments and dropsondes to cover the regional evolution of cloud and thermodynamic processes. Polar 5 carried a similar remote sensing payload as HALO, and Polar 6 was instrumented with in-situ cloud, aerosol, and trace gas instruments focusing on the initial air mass transformation close to the MIZ. The processed, calibrated, and validated data are published in the World Data Center PANGAEA as instrument-separated data subsets and listed in aircraft-separated collections for HALO (Ehrlich et al., 2024a), Polar 5 (Mech et al., 2024a), and Polar 6 (Herber et al., 2024). A detailed overview of the available data sets is provided here. Furthermore, the campaign-specific instrument setup, the data processing, and data quality are summarized. Based on measurements conducted during a specific CAO, it is shown that the scientific analysis of the HALO– (AC)3 data benefits from the coordinated operation of the three aircraft. [ABSTRACT FROM AUTHOR]

Marine cold air outbreaks (MCAOs) strongly affect the Arctic water cycle and, thus, climate through large-scale air mass transformations. The description of air mass transformations is still challenging partly because previous observations do not resolve fine scales, particularly for the initial development of a MCAO, and lack information about cloud microphysical properties. Therefore, we focus on the crucial initial development within the first 200 km over open water of two MCAO events with different strengths observed during the HALO-(AC)3 campaign. Based on unique sampling of high-resolution airborne remote sensing and in-situ measurements, the development of the boundary layer, formation of clouds, onset of precipitation, and riming are studied. For this purpose, we establish a novel approach, solely based on radar reflectivity measurements, to detect roll circulation that forms cloud streets. The two MCAO events observed in April 2022 just three days apart occurred under relatively similar thermodynamic conditions. However, for the first event, colder airmasses from the central Arctic led to a marine cold air outbreak index twice that high as for the second event. Thus, the two cases exhibit different properties of clouds, riming, and roll circulations though the width of the roll circulation is similar. For the stronger MCAO, cloud tops are higher, more liquid-topped clouds exist, the liquid layer at cloud top is wider, and the liquid water path, mean radar reflectivity, precipitation rate, and occurrence are increased. These parameters evolve with distance over open water, as seen by, e.g., boundary layer deepening and cloud top height rising. Generally, cloud streets form after traveling 15 km over open water. After 20 km, this formation enhances cloud cover to just below 100 %. After around 30 km, precipitation forms, though for the weaker event, the development of precipitation is shifted to larger distances. For the stronger event, we detect riming for cloud temperatures below -20 °C. The variability of rime mass has the same horizontal scales as the roll circulation implying the importance of roll circulation on precipitation. The detailed observations of the two MCAO events could serve as a valuable reference for future model intercomparison studies. [ABSTRACT FROM AUTHOR]

The global warming is amplified in the Arctic. To collect data that help to constrain weather and climate models, which often do not realistically represent the enhanced Arctic warming, the HALO-(AC)³ aircraft campaign was conducted in March and April 2022 over the Norwegian and Greenland Seas, the Fram Strait, and the central Arctic Ocean. Observations were made over areas of open ocean, the marginal sea ice zone, and the central Arctic sea ice. Two low-flying and one long-range, high-altitude research aircraft have been employed. Whenever possible, the three aircraft were flown in collocated formation. The campaign focused on one specific challenge posed by the models: The reasonable representation of transformations of air masses during their meridional transport into (northward by moist and warm air intrusions, WAIs) and out of (southward via marine cold air outbreaks, CAOs) the Arctic. To observe the air mass transformations, a quasi-Lagrangian flight strategy using trajectory calculations was realized enabling to sample the moving air mass parcels twice along their trajectories. Eight distinct WAI and 12 CAO cases were probed extensively. From the quasi-Lagrangian measurements, we have derived the diabatic heating and moistening of the moving air masses during CAOs and WAIs, the development of cloud macrophysical and microphysical properties along the southward pathways of the air masses during CAOs, and the moisture budget of WAIs. As an example result, we have obtained typical values of the surface-driven diabatic heating between 1–3 K h-1 and of the near-surface moistening between 0.05–0.3 g kg-1 h-1 within the lowest about 0.5 km. From the observations of WAIs, a weak diabatic cooling of up to 0.4 K h-1 and a moisture loss of up to 0.1 g kg-1 h-1 from the ground to about 5 km altitude were derived. In addition, we discuss the frequency of occurrence of the different thermodynamic phases of Arctic low-level clouds, the interaction of Arctic cirrus with sea ice, water vapor, and aerosol particles, and the characteristic microphysical and chemical properties of Arctic aerosol particles. Finally, we provide proof of a concept to measure mesoscale divergence and subsidence in the Arctic using data from dropsondes released during circular flight patterns. [ABSTRACT FROM AUTHOR]

Upcoming submillimeter wave satellite missions require an improved understanding of the sea ice emissivity to separate atmospheric and surface microwave signals under dry polar conditions. This work investigates hectometer-scale airborne sea ice emissivity observations between 89 and 340 GHz combined with high-resolution visual imagery from two Arctic airborne field campaigns in summer 2017 and spring 2019 northwest of Svalbard, Norway. We identify four distinct sea ice emissivity spectra through K-Means clustering, which occur predominantly over multiyear ice, first-year ice, young ice, and nilas. Nilas features the highest, and multiyear ice features the lowest emissivity among the clusters. Each cluster exhibits similar nadir emissivity distributions from 183 to 340 GHz. To relate hectometer-scale airborne to kilometer-scale satellite footprints, we quantify the reduction of airborne emissivity variability with increasing footprint size. At 340 GHz, the emissivity interquartile range decreases by almost half from the hectometer scale to a footprint of 16 km, typical for satellite instruments. Furthermore, we collocate the airborne observations with polar-orbiting satellite observations. After resampling, the absolute relative bias between airborne and satellite emissivities at similar channels lies below 3 %. Additionally, spectral nadir emissivity variations on the satellite scale are low, with slightly decreasing emissivity from 183 to 243 GHz, which occurs for all hectometer-scale clusters except for predominantly multiyear ice. Our results will enable the development of microwave retrievals and assimilation over sea ice from current and future satellite missions such as Ice Cloud Imager (ICI) and European Polar System (EPS) Sterna. [ABSTRACT FROM AUTHOR]

Riming is a key precipitation formation process in mixed-phase clouds which efficiently converts cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC) 3 aircraft campaign, where two aircraft collected radar and in situ measurements that were closely spatially and temporally collocated over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse optimal estimation algorithm for the retrieval of the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments (combined method). The second method relies on in situ observations only, relating the normalized rime mass to optical particle shape measurements (in situ method). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.024 and 0.021 (mean values of 0.035 and 0.033) for the combined and in situ method, respectively. Assuming that particles with a normalized rime mass smaller than 0.01 are unrimed, we obtain average rimed fractions of 88 % and 87 % over all collocated flight segments. Although in situ measurement volumes are in the range of a few cubic centimeters and are therefore much smaller than the radar volume (about 45 m footprint diameter at an altitude of 500 m above ground, with a vertical resolution of 5 m), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We show the performance of the methods in a case study of a collocated segment of cold-air outbreak conditions and compare normalized rime mass results with meteorological and cloud parameters. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. The methods presented improve our ability to quantify riming from aircraft observations. [ABSTRACT FROM AUTHOR]

During the EUREC4A field study, microwave radiometric measurements were performed at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian in the downstream winter trades of the North Atlantic. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January and 14 February 2020 in which all instruments were operational. Multi-channel radiometric measurements were performed at BCO and aboard RV Meteor between 22 and 31 GHz (K-band) and from 51 to 58 GHz (V-band). Combined radar–radiometer measurements of a W-band Doppler radar with a single-channel radiometer instrument were conducted at 89 GHz aboard RV Meteor and RV Maria S Merian. We present a novel retrieval method to retrieve LWP from single-channel 89 GHz measurements, evaluate retrieved quantities with independent measurements, and analyze retrieval uncertainties by site and instrument intercomparison. Mean IWV conditions of 31.8 kgm-2 match independent radiosoundings at BCO with a root-mean-square difference of 1.1 kgm-2. Mean LWP conditions in confidently liquid cloudy, non-precipitating conditions ranged between 63.1 gm-2 at BCO and 46.8 gm-2 aboard RV Maria S Merian. Aboard the ships, 90 % of LWP was below 120 gm-2 with a 30 % uncertainty for LWP of 50 gm-2. Up to 20 % of confidently liquid cloudy profiles ranged below the LWP detection limit due to optically thin clouds. The data set comprises of processed raw data (Level 1), full quality-controlled post-processed instrument data (Level 2), a unified temporal resolution (Level 3), and a ready-to-use multi-site time series of IWV and LWP (Level 4), available to the public via AERIS (https://doi.org/10.25326/454##v2.0 ;). The data set complements the airborne LWP measurements conducted during EUREC4A and provides a unique benchmark tool for satellite evaluation and model–observation studies. [ABSTRACT FROM AUTHOR]

Due to their potential to either warm or cool the surface, liquid-phase clouds and their interaction with the ice-free and sea-ice-covered ocean largely determine the energy budget and surface temperature in the Arctic. Here, we use airborne measurements of solar spectral cloud reflectivity obtained during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign in summer 2017 and the Arctic Amplification: FLUXes in the Cloudy Atmospheric Boundary Layer (AFLUX) campaign in spring 2019 in the vicinity of Svalbard to retrieve microphysical properties of liquid-phase clouds. The retrieval was tailored to provide consistent results over sea-ice and open-ocean surfaces. Clouds including ice crystals that significantly bias the retrieval results were filtered from the analysis. A comparison with in situ measurements shows good agreement with the retrieved effective radii and an overestimation of the liquid water path and reduced agreement for boundary-layer clouds with varying fractions of ice water content. Considering these limitations, retrieved microphysical properties of clouds observed over the ice-free ocean and sea ice in spring and early summer in the Arctic are compared. In early summer, the liquid-phase clouds have a larger median effective radius (9.5 µ m), optical thickness (11.8) and effective liquid water path (72.3 g m -2) compared to spring conditions (8.7 µ m, 8.3 and 51.8 g m -2 , respectively). The results show larger cloud droplets over the ice-free Arctic Ocean compared to sea ice in spring and early summer caused mainly by the temperature differences in the surfaces and related convection processes. Due to their larger droplet sizes, the liquid clouds over the ice-free ocean have slightly reduced optical thicknesses and lower liquid water contents compared to the sea-ice surface conditions. The comprehensive dataset on microphysical properties of Arctic liquid-phase clouds is publicly available and could, e.g., help to constrain models or be used to investigate effects of liquid-phase clouds on the radiation budget. [ABSTRACT FROM AUTHOR]

Riming is a key precipitation formation process in mixed-phase clouds by efficiently converting cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC)3 aircraft campaign, where two aircraft were collecting spatially and temporally closely collocated radar and in situ measurements over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse Optimal Estimation algorithm to retrieve the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments ('combined method'). The second method relies on in situ observations only, by relating the normalized rime mass to optical particle shape measurements ('in situ method'). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.018 and 0.016 (mean values of 0.027 and 0.028) for combined and in situ method, respectively. Assuming particles with a normalized rime mass smaller 0.01 to be unrimed, we obtain average rimed fractions of 77 % and 75 %. Although in situ measurement volumes are in the range of a few cm3 and therefore much smaller than the radar volume (about 45 m footprint diameter), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We compare normalized rime mass results with meteorological and cloud parameters and show the performance of the methods in two case studies, 1) a collocated segment in cold air outbreak conditions and 2) an in situ only flight close to a polar low. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. We also observe rimed particles in regions without liquid water, suggesting that particles were rimed in a liquid layer above and precipitated. The methods presented improve our ability to quantify riming from aircraft observations. [ABSTRACT FROM AUTHOR]

Riming is a key precipitation formation process in mixed-phase clouds by efficiently converting cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC) 3 aircraft campaign, where two aircraft were collecting spatially and temporally closely collocated radar and in situ measurements over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse Optimal Estimation algorithm to retrieve the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments ("combined method"). The second method relies on in situ observations only, by relating the normalized rime mass to optical particle shape measurements ("in situ method"). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.018 and 0.016 (mean values of 0.027 and 0.028) for combined and in situ method, respectively. Assuming particles with a normalized rime mass smaller 0.01 to be unrimed, we obtain average rimed fractions of 77% and 75%. Although in situ measurement volumes are in the range of a few cm³ and therefore much smaller than the radar volume (about 45 m footprint diameter), we assume they are representative of the radar volume.When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We compare normalized rime mass results with meteorological and cloud parameters and show the performance of the methods in two case studies, 1) a collocated segment in cold air outbreak conditions and 2) an in situ only flight close to a polar low.We find that higher normalized rime masses correlate with streaks of higher radar reflectivity.We also observe rimed particles in regions without liquid water, suggesting that particles were rimed in a liquid layer above and precipitated. The methods presented improve our ability to quantify riming from aircraft observations. [ABSTRACT FROM AUTHOR]

Most Arctic clouds occur below 2 km altitude, as revealed by CloudSat satellite observations. However, recent studies suggest that the relatively coarse spatial resolution, low sensitivity, and blind zone of the radar installed on CloudSat may not enable it to comprehensively document low-level clouds. We investigate the impact of these limitations on the Arctic low-level cloud fraction, which is the number of cloudy points with respect to all points as a function of height, derived from CloudSat radar observations. For this purpose, we leverage highly resolved vertical profiles of low-level cloud fraction derived from down-looking Microwave Radar/radiometer for Arctic Clouds (MiRAC) radar reflectivity measurements. MiRAC was operated during four aircraft campaigns that took place in the vicinity of Svalbard during different times of the year, covering more than 25 000 km. This allows us to study the dependence of CloudSat limitations on different synoptic and surface conditions. A forward simulator converts MiRAC measurements to synthetic CloudSat radar reflectivities. These forward simulations are compared with the original CloudSat observations for four satellite underflights to prove the suitability of our forward-simulation approach. Above CloudSat's blind zone of 1 km and below 2.5 km , the forward simulations reveal that CloudSat would overestimate the MiRAC cloud fraction over all campaigns by about 6 percentage points (pp) due to its horizontal resolution and by 12 pp due to its range resolution and underestimate it by 10 pp due to its sensitivity. Especially during cold-air outbreaks over open water, high-reflectivity clouds appear below 1.5 km , which are stretched by CloudSat's pulse length causing the forward-simulated cloud fraction to be 16 pp higher than that observed by MiRAC. The pulse length merges multilayer clouds, whereas thin low-reflectivity clouds remain undetected. Consequently, 48 % of clouds observed by MiRAC belong to multilayer clouds, which reduces by a factor of 4 for the forward-simulated CloudSat counterpart. Despite the overestimation between 1 and 2.5 km , the overall low-level cloud fraction is strongly reduced due to CloudSat's blind zone that misses a cloud fraction of 32 % and half of the total (mainly light) precipitation amount. [ABSTRACT FROM AUTHOR]

In this study, we analyse the contribution of atmospheric rivers (ARs), cyclones, and fronts to the total precipitation in the Arctic. We focus on two distinct periods of different weather conditions from two airborne campaigns: ACLOUD (Arctic Cloud Observations Using airborne measurements during polar day; May/June 2017) and AFLUX (Aircraft campaign Arctic Boundary Layer Fluxes; March/April 2019). Both campaigns covered the northern North Atlantic sector, the area in the Arctic that is affected by the highest precipitation rates. Using ERA5 reanalysis, we identify pronounced regional anomalies with enhanced precipitation rates compared to the climatology during ACLOUD due to these weather systems, whereas during AFLUX enhanced precipitation rates occur over most of the area. We have established a new methodology that allows us to analyse the contribution of ARs, cyclones, and fronts to precipitation rates based on ERA5 reanalysis and different detection algorithms. Here, we distinguish whether these systems occur co-located or separately. The contributions differ between the two periods. During ACLOUD (early summer), the precipitation rates are mainly associated with AR- (40 %) and front-related (55 %) components, especially if they are connected, while cyclone-related components (22 %) play a minor role. However, during AFLUX (early spring) the precipitation is mainly associated with cyclone-related components (62 %). For both campaign periods, snow is the dominant form of precipitation, and the small rain occurrence is almost all associated with ARs. About one-third of the precipitation can not be attributed to one of the weather systems, the so-called residual. While the residual can be found more frequently as convective than as large-scale precipitation, the rare occasion of convective precipitation (roughly 20 %) can not completely explain the residual. The fraction of precipitation classified as residual is reduced significantly when a precipitation threshold is applied that is often used to eliminate "artificial" precipitation. However, a threshold of 0.1 mm h -1 reduces the total accumulated precipitation by a factor of 2 (ACLOUD) and 3 (AFLUX), especially affecting light precipitation over the Arctic Ocean. We also show the dependence of the results on the choice of the detection algorithm serving as a first estimate of the uncertainty. In the future, we aim to apply the methodology to the full ERA5 record to investigate whether the differences found between the campaign periods are typical for the different seasons in which they were performed and whether any trends in precipitation associated with these weather systems can be identified. [ABSTRACT FROM AUTHOR]